Postdoctoral Research Fellow (3 years) in Multi-Sensor and Deep Learning for Large-Scale Remote Sensing

The Department of Physics and Technology, The Arctic University of Norway (UiT), Tromsø, Norway
Deadline: December 9, 2018

The Department of Physics and Technology announces a vacant position of Postdoctoral Research Fellow in the area of multi-sensor and deep learning for applications in large-scale remote sensing sea ice mapping at UiT The Arctic University of Norway, Faculty of Science and Technology.

The umbrella ExtremeEarth project is about transforming the long time series of Synthetic Aperture Radar (SAR) and multispectral images acquired by the constellations of Sentinel-1/2/3 satellites into valuable information. The project shall investigate strategies and develop scalable deep learning algorithms for multi-sensor surface cover mapping based on Copernicus Big Data. Over the polar regions, this technology will be applied to perform long-term temporal and large-scale spatial characterization of the sea ice cover and its complicated internal dynamics.

The appointment is for a period of three years with the possibility of up to one year’s extension.

The successful candidates will work at CIRFA. CIRFA does research on integrated remote sensing for Arctic operations by developing data analysis methods and technologies for reliably characterizing and monitoring the physical environment of the Arctic. The Centre also explores methods to efficiently assimilate the derived information into models to perform improved predictions of sea ice state, meteorological and oceanographic conditions. See more at http://cirfa.uit.no/.

 

Qualification requirements

This position requires a Norwegian doctoral degree within a field relevant for the research theme of the position (i.e. physics, machine learning, mathematics, statistics, or computer science), or a corresponding foreign doctoral degree recognised as equivalent to a Norwegian doctoral degree.

 

We are looking for a strongly motivated person, who has an excellent academic record and potential, with analytical and problem-solving skills. The suitable candidate should have expertise in:

  • machine learning and/or deep learning;
  • computer science and programming;
  • remote sensing and big data analysis;
  • image processing and statistics.

Moreover, the candidate should show a good command of English, both spoken and written. The following skills would also be advantageous:

  • Principles of information theory;
  • Previous experience with sea ice remote sensing;
  • International experience.

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